The present invention relates generally to image systems and, more particularly, to matching the contrast of multiple images from the image system.
Many types of digital imaging systems are known. In the medical field, such systems may include CT systems, X-ray system and MRI systems. In each case multiple digital images may be formed of the same scene or object. The multiple images may be generated using the same input with different parameter sets. In many circumstances there exists a need to evaluate which of these images are optimal so that the appropriate parameters can be obtained. However, the problem with such images is that the brightness and contrast are different. Thus, the images have to be mentally normalized. That is, brightness and contrast differences must be overlooked by the evaluator. This kind of normalization may lead to subjective bias and takes the mind of the evaluator away from the parameter evaluation.
Image processing algorithms are available in which different parameter choices produce different looks. For example, one set of parameters yields improved smoothness but produces artificially bright undesirable regions. The other set of parameters produces noisy images but without bright regions. Adjusting each image individually is time consuming and may yield inconsistent results.
It would be desirable to match the brightness and contrast of various types of images such as smooth images and noise images to produce resultant images that are smooth but not artificially bright in one region. Also, there exists a need to match images of the same scene taken at multiple time points such that they can be displayed with the same brightness and contrast.